Fourier transform infrared (FTIR) spectroscopy is a known technique for the identification of microorganisms (Mariey et al., 2001 Vibr. Spectrosc. 26:151). Infrared (IR) spectroscopy measures the vibrations of chemical bonds within all the biochemical constituents of cells, i.e., proteins, lipids, polysaccharides, and nucleic acids, and provides quantitative information about the total biochemical composition of the intact whole microorganism. Furthermore, because the IR spectra of microorganisms consist of distinct and unique patterns the spectra effectively serve as “fingerprints,” allowing for their use in taxonomic discrimination. Indeed, the use of IR spectroscopy as a means of differentiating and identifying bacteria was extensively reported as early as the 1950s. However, it was concluded at that time that, although individual strains of bacteria definitely exhibit unique IR spectra, the identification of bacteria by IR spectroscopy could not be regarded as a useful technique, as the procedure was too time-consuming and impractical. Indeed, reports on the study of microorganisms by IR spectroscopy became less frequent in the 1960s and virtually ended in the mid-1970s.
Interest in this technique revived in the early 1990s, when the development of FTIR spectroscopy in combination with the emergence of chemometric techniques for the analysis of FTIR data opened a wide range of new applications for IR spectroscopy (Griffiths and Chalmers eds, 2001 Handbook of vibrational spectroscopy, John Wiley & sons, New-York, vol. 5). Beginning with the pioneering work by Naumann and co-workers in Germany (Naumann et al., 1991 Nature, 351:81; Helm et al., 1991 J. Gen. Microbiol. 137:69), FTIR spectroscopy has been demonstrated within the past decade to be useful for microbial analysis (Naumann, 2000 infrared spectroscopy in microbiology, in: R. A. Meyers (eds) encyclopedia of analytical chemistry, Wiley, Chichester pp. 102-131). The method is uniformly applicable to virtually all microorganisms that can be grown in culture.
Suggested potential microbiological applications of FTIR spectroscopy include (i) identification of life-threatening pathogens in the clinical laboratory: (ii) epidemiological investigations, conductance of case studies, screening of pathogens, hygiene control, elucidation of infection chains, therapy control, and detection of recurrent infections; (iii) characterization and screening of microorganisms from the environment; (iv) monitoring of biotechnological processes; (v) microbiological quality control in the food and pharmaceutical industries; and (vi) maintenance of strain collections.
The fundamental requirement for FTIR identification of microorganisms is that the variance within the spectra of one taxon must be smaller than the variance among spectra of different taxa. Although the variations in biochemical composition among different taxa do result in differences in their IR spectra, these differences may be very slight (e.g., between different strains). Thus, the above requirement imposes stringent conditions on spectral reproducibility, and interest in IR bacteria identification waned in the 1960s largely because these conditions could not be achieved with the IR instrumentation available at the time
The reproducibility of the sample-handling technique employed to acquire the FTIR spectra of bacteria is also of critical importance. Analysis of IR spectra to determine identification of microorganisms by providing a fingerprint has been used in the past. However, such analyses have yielded relatively poor reproducibility and identification success rate. FTIR spectra of bacteria are normally recorded by depositing cells suspended in saline solution on an optical window (e.g., ZnSe) and drying the sample to form a bacterial film. Spectral variability results from differences in the distribution of the cells on the IR window, thickness of bacterial film, moisture content of the film and the like.
FTIR spectra of microorganisms are commonly acquired in the transmission mode, although various other techniques such as attenuated total reflectance (ATR) and diffuse reflectance spectroscopy (DRIFT) have also been employed. For spectra acquired in the transmission mode, spectral reproducibility depends mainly on the uniformity of the sample (sample homogeneity, particle size) and sample thickness (or pathlength). Sample nonuniformity leads to baseline variations owing to the scattering, diffraction, and refraction that occur as the IR beam passes through the sample, whereas variations in sample thickness result in variations in band intensity, although consistency in relative peak intensities is maintained.
Conventional IR methods for bacterial identification have a number of additional drawbacks. For example bacterial cells must be extensively cultured prior to FTIR analysis to increase the overall biomass and then transferred from the growth media onto an IR-transparent optical window, an IR-reflecting substrate, or an IR internal reflection element for spectral collection in the transmission mode, transmission-reflection, or attenuated total reflectance mode, respectively. Both these steps represent bottlenecks that have prevented the speed advantages of FTIR bacteria identification from being fully exploited. Furthermore, they make building a spectral library a laborious and time consuming process, which likely accounts, in part, for the lack of commercial bacterial infrared spectral databases that would be required in order for FTIR bacteria identification to be implemented in routine microbiological analysis.
U.S. Pat. No. 5,660,998 to Naumann and Labischinski describes a method for identifying bacteria by obtaining IR spectra of small colonies. The colonies of between 50 to 4,000 cells are deposited on a surface, localized with a microscope and a spectrum of each colony is obtained. However, when microorganisms are deposited on a surface or suspended in a solution for acquisition of spectral data, there usually results an inhomogeneous distribution of the microorganisms within the sample. Conventional acquisition of spectral data does not discriminate regions of inhomogeneities and therefore provides an “average” signal, which may comprise signal contributions that render the spectral information less reliable for identifying microorganisms. Furthermore, bacterial colonies, even when originating from a pure strain, may exhibit physiological and biochemical variability that can influence the reproducibility of the spectral data.
There is therefore a need for improved methods for identifying microorganisms using spectral data.